You can manage bookmarks using lists, please log in to your user account for this.
Media type:
E-Article
Title:
Using probabilistic reasoning to automate software tuning
Contributor:
Sullivan, David G.;
Seltzer, Margo I.;
Pfeffer, Avi
imprint:
Association for Computing Machinery (ACM), 2004
Published in:ACM SIGMETRICS Performance Evaluation Review
Language:
English
DOI:
10.1145/1012888.1005739
ISSN:
0163-5999
Origination:
Footnote:
Description:
<jats:p>Manually tuning the parameters or "knobs" of a complex software system is an extremely difficult task. Ideally, the process of software tuning should be automated, allowing software systems to reconfigure themselves as needed in response to changing conditions. We present a methodology that uses a probabilistic, graphical model known as an influence diagram as the foundation of an effective, automated approach to software tuning. We have used our methodology to simultaneously tune four knobs from the Berkeley DB embedded database system, and our results show that an influence diagram can effectively generalize from training data for this domain.</jats:p>